Perhaps most importantly – with the advent of machine learning – machines perpetually remain on the learning curve. The old axiom “you can’t teach an old dog new tricks” does not apply to machines.

Many tasks lend themselves well to “machine-led” environments (by “machine-led” we refer to discrete tasks and complex workflows that have or could have machine learning and/or artificial intelligence as a core underpinning). For these tasks, humans will add value by providing machines with access to data sets that machines could not acquire on their own. The saying “feed the beast” will have never been truer.

However, there are instances where machine-led processes are not optimal. For example: great works of art, music and other forms of inspired creativity and original thinking where the outcome isn’t clear.

We are inspired to create when we are inspired to create. Would a sentient machine be inspired to create the Mona Lisa? Would a sentient machine be inspired to put people on Mars as Elon Musk wishes to do? (more likely that a machine would only pursue colonization of Mars when it would be practical to pursue that outcome as a result of an event or series of events here on earth). Would a sentient machine have been motivated to create electric vehicles?

Count me an optimist in that I believe that the most strategic, creative endeavors will always benefit greatly from human participation and leadership.